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• W3136648924 startingPage "102467" @default.
• W3136648924 abstract "Nowadays to improve the dynamic performance of the power system and control the frequency stability, load frequency control (LFC) based on droop strategy must be provided. PID controller is also used in addition to the droop method to maintain the stable load frequency. In the new power systems such as microgrids (MGs) with different low and high-inertial distributed generators (DGs), using only LFC method is not sufficient to provide the stable load frequency and balanced power sharing. Thus, modified LFC approach is needed. Energy storage element is a precious solution presented to combat the non-desirable transient conditions on load frequency and power sharing. Among different storage elements, superconducting magnetic energy storage (SMES) is selected in this paper because of fast dynamic response and desirable inertial characteristic. Using accurate modeling of SMES, the reserved power in off-peak times can be exploited in on-peak times to inject the required power in sudden load changes to provide stable frequency and balanced power sharing. Moreover, the uncertainty of renewable DGs such as photovoltaic (PV) and wind turbine (WT) can be assumed as disturbance input to the MG. Applying SMES in the MG, accurate modeling of SMES dynamic behavior in control block and modeling of DGs uncertainties with suitable probability functions in the proposed control structure leads to more stable LFC approach shown in simulation results of this paper. Inertial property improvement by SMES is also analyzed while comparing with other LFC methods, proposed modified LFC approach presents more stable load frequency. In addition, the frequency fluctuation in the proposed control structure is reduced 15–20% in average compared to other methods." @default.
• W3136648924 created "2021-03-29" @default.
• W3136648924 creator A5057691571 @default.
• W3136648924 date "2021-05-01" @default.
• W3136648924 modified "2023-10-16" @default.
• W3136648924 title "Load frequency control and dynamic response improvement using energy storage and modeling of uncertainty in renewable distributed generators" @default.
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• W3136648924 doi "https://doi.org/10.1016/j.est.2021.102467" @default.
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